Click to see Equity Center Data Team contributors



Data Collection Process | Data Collections | Examples

Data Collection Process

In the summer of 2021, we began creating and refining a replicable data collection process to build a collection of data resources for use in our collective work and by anyone in the community. The process is intended to make this work transparent, to provide resources for other to use, and to be highly automated for easier updates.

Based on the needs and requests for additional information and data from within our coalition, and those articulated by additional community partners, we

  1. Researched available sources, seeking to understand the provenance and genesis of the data (e.g., collected via surveys, captured from satellite imagery, derived from models built around station monitors, etc.), how frequently is it updated, what areas is it available for or could it be aggregated to, and the available variables and measures within the initial sources.
  2. Wrote code to acquire the data from source, working to remove as many manual steps as possible; to process the data, filtering to our region, checking data quality, deriving additional measures from included variables, aggregating to administrative boundaries for integration with demographic and population data. Output includes replication code and a csv file of the resulting data.
  3. Created code to build a documentation file identifying the source of the data, providing variable definitions, and generating initial visualization of the key metrics. Output includes replication code and a web document providing more details about the data source.

While continuing to add to the current data collections and clean up and refine our work to date, we began step (4) in the spring, integrating the data sources for further analysis and visualization. That work is represented in this atlas and the data stories created for the Picturing Climate exhibit.

Newly Available Data Collections

To build on the the population data we’ve collected as part of the broader Equity Atlas Prototype (e.g., demographic, economic, health, and other social data) and Shelter in Place measures (e.g., food, car, broadband access), the table below provides an overview of the data collections, including data sources, key measures, and motivating questions. The table can be filtered for key topics (climate measures, risk factors, community assets and infrastructure, transportation).

Click to see Topic Icon details



Below, we provide examples of a few of the data source represented above.

Data Examples

Percent Energy Burdened by Census Tract

Household energy burden is calculated as the percent of income spent on energy. A household energy burden of 6% or more is defined a energy burdened. Here we show the percent of households within a census tract estimated to be energy burdened based on the Low-Income Energy Affordability Data, 2018 Update.

Charlottesville

Albemarle County

Census tract 109.03 containing primarily student housing has been omitted

Fluvanna County

Greene County

Louisa County

Nelson County

Commute Patterns

The Origin-Destination Employment Statistics (LODES) pairs the census blocks where employees live and work, allowing us to estimate outcomes like the average commuting distance of residents in the Charlottesville region and the most common places where non-Charlottesville region residents who work here call home.

Commuting Distances within the Charlottesville Region

The map below shows the average commuting distance for people who both live and work in the Charlottesville region by census block group.

Commuting Sources Outside the Charlottesville Regio

Here we show where individuals who work in the Charlottesville region but live outside of it reside. The figure below shows only the number of commuters from localities with more than 1000 Charlottesville region workers.

The highest number of non-region residents are coming from Augusta County.

Surface Temperature: Charlottesville

Using Landsat8 satellite imagery, we extracted the estimated surface temperature for each 100-meter pixel and aggregated these estimates into census blocks, block groups, and tracts. Below we show the median measured surface temperature with each block on as measured on 08/24/2021 at 11:53am EST.

The Land Surface Temperature (LST) is the radiative skin temperature on the ground, not the temperature as experienced by people or as measured by air temperature monitors.

Temperature over Time

Using NOAA’s Climate Divisional Dataset from the National Center For Environmental Information, we visualize changes in temperature in the Charlottesville region localities over time.

Average Maximum Temperatures, Annually

This is the average of the maximum temperature recorded across all months for each year.

Maximum Temperatures, July

Here we show the maximum July temperature measured in each year.